<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of public opinion and the direction of the debate regarding old and new fintech technologies. The results of the study show that the SVM algorithm has an average accuracy of 87.32% and the NB algorithm has an average accuracy of 81.56% in testing the sample data in a comparison of old and new fintech technology on the internet. The study tested data in a comparison of two specific arguments, namely the debate about which technology is more efficient in old and new fintech on the internet. Despite many unresolved arguments, the study successfully proved that new fintech is more preferred than old fintech, with 71% positive sentiment directed towards new fintech. However, the dataset also found that 62% negative sentiment is directed towards new fintech, indicating that although new fintech is more preferred, there are still some issues that need to be addressed. One reason for negative sentiment towards new fintech may be the continued concerns about security and privacy of user data. Furthermore, other factors that may cause negative sentiment towards new fintech include a lack of understanding about how the technology works.</p>
</abstract>

The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of public opinion and the direction of the debate regarding old and new fintech technologies. The results of the study show that the SVM algorithm has an average accuracy of 87.32% and the NB algorithm has an average accuracy of 81.56% in testing the sample data in a comparison of old and new fintech technology on the internet. The study tested data in a comparison of two specific arguments, namely the debate about which technology is more efficient in old and new fintech on the internet. Despite many unresolved arguments, the study successfully proved that new fintech is more preferred than old fintech, with 71% positive sentiment directed towards new fintech. However, the dataset also found that 62% negative sentiment is directed towards new fintech, indicating that although new fintech is more preferred, there are still some issues that need to be addressed. One reason for negative sentiment towards new fintech may be the continued concerns about security and privacy of user data. Furthermore, other factors that may cause negative sentiment towards new fintech include a lack of understanding about how the technology works.

Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution 4.0 International License.

The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and...

Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms

Published Online: Dec 06, 2023

Page range: 373 - 380

Received: Dec 01, 2022

Accepted: Oct 01, 2023

DOI: https://doi.org/10.2478/mspe-2023-0041

Keywords
Fintech, SVM, Sentiment Analysis, NB

© 2023 Tubagus Asep Nurdin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms

Published Online: Dec 06, 2023

Page range: 373 - 380

Received: Dec 01, 2022

Accepted: Oct 01, 2023

DOI: https://doi.org/10.2478/mspe-2023-0041

KeywordsFintech, SVM, Sentiment Analysis, NB

© 2023 Tubagus Asep Nurdin et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Fintech, SVM, Sentiment Analysis, NB